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Lead Risk and Fraud Strategy Analyst

2 months ago

Jackson, Mississippi, United States Intuit Full time

About Intuit QuickBooks
Intuit QuickBooks is dedicated to empowering small businesses by streamlining their financial processes, allowing entrepreneurs to concentrate on their core operations.

Position Overview
We are in search of a skilled quantitative risk strategy leader with extensive experience in risk management and payment systems. This individual will be tasked with crafting risk solutions that promote quicker and more effective decision-making, ultimately fostering sustainable growth for the business.

This role is part of a dynamic, innovative team that is passionate about transforming the payment experience for small and medium-sized businesses (SMBs), ensuring they find it indispensable to move away from traditional methods.

Key Responsibilities
- Drive the fraud risk components of various business initiatives and respond to fraud-related challenges.
- Utilize advanced analytical methods to analyze large-scale account and transaction data, developing and refining fraud risk strategies and translating them into actionable business plans.
- Oversee the complete cycle of risk strategy and policy development, from identifying opportunities and creating action plans to policy testing, implementation, and performance monitoring.
- Cultivate expertise in various risk types associated with financial transactions to balance risk management with growth within the Intuit ecosystem.
- Collaborate closely with data scientists, risk operations, product teams, data engineering, and analytics to enhance customer segmentation, innovate risk strategies, and conduct portfolio analyses.
- Evaluate and recommend third-party data providers to address individual and business risk exposures.
- Engage in continuous analysis and research using diverse tools to enhance risk mitigation techniques.

Qualifications
- A Master's or PhD in quantitative disciplines such as Statistics, Mathematics, Finance, Economics, or Operations Research, along with a minimum of 2 years of relevant experience in data analytics or data science. Alternatively, a Bachelor's degree in these fields with at least 4 years of experience is acceptable.
- Proficiency in SQL, Python, Tableau, and Excel, with a working knowledge of A/B testing considered a plus.
- Strong analytical and problem-solving capabilities, familiar with statistical modeling, loss forecasting, and collections.
- Understanding of payment processing fundamentals and awareness of industry fraud and risk trends is advantageous.
- Proven ability to extract insights from data to meet business needs through both quantitative and qualitative analysis.
- A genuine passion for data analysis and a relentless curiosity to comprehend complex business challenges while seeking innovative solutions.

Personal Attributes
- Exceptional storytelling ability with data, capable of effectively educating stakeholders and instilling confidence to drive action based on recommendations.
- Adaptable to a fast-paced work environment, skilled in multitasking, and able to balance immediate and long-term strategic goals to achieve business objectives.